Genome-wide association mapping for grain manganese in rice (Oryza sativa L.): using a multi-experiment approach

Panthita Ruang-areerate* (Corresponding Author), Anthony Travis, Shannon R. M. Pinson, Lee Tarpley, Georgia C. Eizenga, Mary Lou Guerinot, David E Salt, Alex Douglas, Adam H. Price, Gareth J Norton

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

Manganese (Mn) is an essential trace element for plants and commonly contributes to human health; however, the understanding of the genes controlling natural variation in Mn in cropplants is limited. Here, the integration of two of genome-wide association study approacheswere used to increase the identification of valuable quantitative trait loci (QTL) and candidategenes responsible for the concentration of grain Mn across 389 diverse rice cultivars grown inArkansas and Texas, USA in multiple years. Single-trait analysis was initially performed using three different SNP datasets. As a result, significant loci could be detected using the high-density SNP dataset. Based on the 5.2M SNP dataset, major QTLs were located on chromosomes 3 and 7 for Mn containing six candidate genes. Additionally, the phenotypic data of grain Mn concentration was combined from three flooded-field experiments from the two sites and three years using multi-experiment analysis based on the 5.2M SNP dataset. wo previous QTLs on chromosome 3 were identified across experiments, whereas new Mn QTLs were identified that were not found in individual experiments, on chromosomes 3, 4, 9 and 11. OsMTP8.1 was identified in both approaches and is a good candidate gene that could
be controlling grain Mn concentration. This work demonstrates the utilisation of multi35 experiment analysis to identify constitutive QTLs and candidate genes associated with the grain Mn concentration. Hence, the approach should be advantageous to facilitate genomic breeding programs in rice and other crops considering QTLs and genes associated with complex traits in natural populations.
Original languageEnglish
JournalHeredity
Publication statusAccepted/In press - 6 Nov 2020

Keywords

  • manganese
  • rice grain
  • QTL
  • GWAS
  • multi-experiment analysis

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